Participatory Political Economy Analysis –
CLS students, farmers, and district level policymakers discuss processes of change in political and economic systems.
by Kawuma Penninah
Day 6 of the Collaborative Learning School gave students the opportunity to facilitate a participatory Political Economy Analysis (PEA). This involved collaborative group activities where the participants examined the interaction between political and economic factors that can influence attempts to solve some of the major livelihood challenges identified in the first week. Ultimately, it served as a valuable discussion generator among key stakeholders (community members that have the power to bring about positive change) and informed policy making.
The workshop was held in a conference room setting, where the attendees included farmers from participating villages, as well as district-level policymakers in key sectors like agriculture, water, energy, economy, and development. We were graced by the attendance of officials from Buikwe District in their various capacities, as well as representatives from the Non-Government Organization (NGO) network. The attending district officials included Dr. Lulume Micheal P Bayigga, a Member of Parliament (MP) of Buikwe South, and Mr. Balaba Dunstan, the Chief Administrative Officer (CAO). Other policy stakeholders included Buikwe District’s Community Development Officer, Production Officer, Agricultural Officer, Environment Officer, District Counselor, as well as a chairperson of Light in the Shadow (an extension NGO). Opening remarks were given by Dr. Florence Birungi (Makerere University), Dr. Michael Jacobson (Penn State University), and Mr. Balaba Dunstan (CAO), who welcomed all attendees and provided an overview of the day’s proceedings.
All students, farmers, and officials were allocated into four groups, corresponding to the villages assigned from the first week. The Political Economy Analyses (PEA) were carried out and these were facilitated completely by students, while officials and farmers were the main participants, listening intently and contributing their knowledge and expertise to the discussion. The PEA was conducted in four steps:
(i). The change we want to bring about
A key lesson that Groups 1 – 4 learned from farmer interviews in Week One was that almost all the main challenges (e.g., water supply, pests and diseases, soil fertility etc.) had solutions that required either: ‘collaboration and capital’ or ‘collaboration and knowledge sharing’. In the first step of PEA, officials and farmers in each group picked one of these two topics as a focus for analysis. They then wrote down the short term (year 1) and long term (year 5) outcomes that they would expect to see if these were to be increased or supplied.
(ii). What is the situation now?
The second step involved analyzing the “current situation” where participants identified the factors and actors that play a role in the community’s ability to bring about positive change. This included factors like climate change, or farmer attitude toward change, and actors like government officials, farmers, financial institutions, or extension workers. These examples and more were drafted onto sticky notes and participants were each prompted to vote for the factors that they believed were most significant to be used in the next step of the analysis.
Photo: An example from the CLS group representing Namukono Village. The change objective discussed was increased collaboration and knowledge sharing. This figure depicts a summary of votes cast by stakeholders regarding the actors and factors having the greatest influence on collaboration and knowledge sharing at village levels.
(iii). What does this mean for our desired change?
Officials and farmers created visual maps of the political economy features that most influenced the desired change. This process was used to identify key relationships between each feature in the political landscape. Different colored markers were used to draw lines connecting certain factors and actors to show which had power or influence over others, and which were connected by working relationships.
Photo: An example from CLS group representing Wabusolo Village. The change objective discussed was increased collaboration and generation of capital. This figure depicts a political economy feature map, including the factors and actors, direct and indirect relationships, as well as the nature of relationships between factors in the system.
(iv). Where can we go now?
In the final step, they analyzed the political economy map from step (iii) and used the analysis to plot routes towards the different desired changes. With the PEA maps it was much easier to visually identify factors/actors that could be powerful entry points for change, and these helped us to create a roadmap for how to achieve it.
Photo: An example from the CLS group representing Lugasa Village. The change objective discussed in this group was increased collaboration and knowledge sharing. This figure depicts current channels of information and knowledge transfer at national, district, sub-county, parish, and village levels.
Upon completing the day’s main task, students from the different groups reported back to the plenary the different findings. A common theme began to emerge, which was the idea that when farmers trust one another, they can share their knowledge and experiences with one another to advance their opportunities because groups have far more power than individuals. They also noted that there is a need for transparency and accountability; accompanied by communication at all levels from farmers to the district so as to ensure that district services reach the farmers. In another group, the farmers identified that they needed to have a positive mindset towards their work as well as monitoring of actions and outcomes along with creating efficient communication amongst themselves.
Photo: An example from the CLS group representing Ddungi Village. This group concluded that stronger farmer networks may improve local livelihood. An increase in access to knowledge and skills was considered necessary to improve cooperative organizing, agronomic practices, and economic development.
The district policymakers gave their reflections. Mr. Balaba Dunstan (CAO) noted that there was a big gap between the extension workers and the farmers yet. He described a great need for collaboration, since the farmers have indigenous knowledge whereas the extension workers have theoretical knowledge. Further, extension workers can only be effective at their job if they have passion for the agricultural field. The CAO gave the audience a phrase: “Whatever you do without us is not for us”.
In his reflection, Dr. Lulume Micheal Bayigga (MP, Buikwe District South) thanked the SustainFood Network for choosing Uganda and Buikwe for this study. He encouraged the community to continue farming for the purpose of wealth generation. He then went ahead to note that farmer groups often fail due to a lack of trust and encouraged them to work together for empowerment both in food production and market access. The MP also acknowledged the linkage the CLS had created between decision makers, primary producers, and implementers together for improved productivity and solving farmers’ problems.
The function was concluded with the team coming together for a group photo with the officials and farmers, after which a very delicious lunch was served for all. Both CLS students and project facilitators considered the day’s events successful. Sincere gratitude is due to all farmers, district level officials, and other policy makers who participated in this successful collaborative workshop. Thank you!
In the afternoon, student groups debriefed to identify: what were the common themes identified by farmers? Which topics were most important to the communities? At what scale (individual, community, federal policy) could solutions to these problems be designed? Tomorrow we will present our brainstorms to the farmers for feedback, a kind of “check and balance” to ensure a two way conversation, and that solutions are developed contextually based on need.
